• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.396-396
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• 2013

The resistive random access memory (ReRAM) has several advantages to apply next generation non-volatile memory device, because of fast switching time, long retentions, and large memory windows. The high mobility of monolayered graphene showed several possibilities for scale down and electrical property enhancement of memory device. In this study, the monolayered graphene grown by chemical vapor deposition was transferred to $SiO_2$ (100 nm)/Si substrate and glass by using PMMA coating method. For formation of metal-oxide nanoparticles, we used a chemical reaction between metal films and polyamic acid layer. The 50-nm thick BPDA-PDA polyamic acid layer was coated on the graphene layer. Through soft baking at $125^{\circ}C$ or 30 min, solvent in polyimide layer was removed. Then, 5-nm-thick indium layer was deposited by using thermal evaporator at room temperature. And then, the second polyimide layer was coated on the indium thin film. After remove solvent and open bottom graphene layer, the samples were annealed at $400^{\circ}C$ or 1 hr by using furnace in $N_2$ ambient. The average diameter and density of nanoparticle were depending on annealing temperature and times. During annealing process, the metal and oxygen ions combined to create $In_2O_3$ nanoparticle in the polyimide layer. The electrical properties of $In_2O_3$ nanoparticle ReRAM such as current-voltage curve, operation speed and retention discussed for applictions of transparent and flexible hybrid ReRAM device.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.115-116
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• 2012

The demand for flexible electronic systems such as wearable computers, E-paper, and flexible displays has increased due to their advantages of excellent portability, conformal contact with curved surfaces, light weight, and human friendly interfaces over present rigid electronic systems. This seminar introduces three recent progresses that can extend the application of high performance flexible inorganic electronics. The first part of this seminar will introduce a RRAM with a one transistor-one memristor (1T-1M) arrays on flexible substrates. Flexible memory is an essential part of electronics for data processing, storage, and radio frequency (RF) communication and thus a key element to realize such flexible electronic systems. Although several emerging memory technologies, including resistive switching memory, have been proposed, the cell-to-cell interference issue has to be overcome for flexible and high performance nonvolatile memory applications. The cell-to-cell interference between neighbouring memory cells occurs due to leakage current paths through adjacent low resistance state cells and induces not only unnecessary power consumption but also a misreading problem, a fatal obstacle in memory operation. To fabricate a fully functional flexible memory and prevent these unwanted effects, we integrated high performance flexible single crystal silicon transistors with an amorphous titanium oxide (a-TiO2) based memristor to control the logic state of memory. The $8{\times}8$ NOR type 1T-1M RRAM demonstrated the first random access memory operation on flexible substrates by controlling each memory unit cell independently. The second part of the seminar will discuss the flexible GaN LED on LCP substrates for implantable biosensor. Inorganic III-V light emitting diodes (LEDs) have superior characteristics, such as long-term stability, high efficiency, and strong brightness compared to conventional incandescent lamps and OLED. However, due to the brittle property of bulk inorganic semiconductor materials, III-V LED limits its applications in the field of high performance flexible electronics. This seminar introduces the first flexible and implantable GaN LED on plastic substrates that is transferred from bulk GaN on Si substrates. The superb properties of the flexible GaN thin film in terms of its wide band gap and high efficiency enable the dramatic extension of not only consumer electronic applications but also the biosensing scale. The flexible white LEDs are demonstrated for the feasibility of using a white light source for future flexible BLU devices. Finally a water-resist and a biocompatible PTFE-coated flexible LED biosensor can detect PSA at a detection limit of 1 ng/mL. These results show that the nitride-based flexible LED can be used as the future flexible display technology and a type of implantable LED biosensor for a therapy tool. The final part of this seminar will introduce a highly efficient and printable BaTiO3 thin film nanogenerator on plastic substrates. Energy harvesting technologies converting external biomechanical energy sources (such as heart beat, blood flow, muscle stretching and animal movements) into electrical energy is recently a highly demanding issue in the materials science community. Herein, we describe procedure suitable for generating and printing a lead-free microstructured BaTiO3 thin film nanogenerator on plastic substrates to overcome limitations appeared in conventional flexible ferroelectric devices. Flexible BaTiO3 thin film nanogenerator was fabricated and the piezoelectric properties and mechanically stability of ferroelectric devices were characterized. From the results, we demonstrate the highly efficient and stable performance of BaTiO3 thin film nanogenerator.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.697-707
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• 2017

In this paper, we propose a modified GARCH(p, q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p, q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1, 1)-X model studied by Han (2015) to various GARCH(p, q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1, 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p, q) model combined with proper additional covariate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.153-158
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• 2019

In this paper, we analyze the infrared feature for the small coast targets according to the surrounding environment for autonomous flight device equipped with an infrared imaging sensor and we propose Cross Duality of Neural Network (CR-DuNN) method which can classify the target and clutter in coastal environment. In coastal environment, there are various property according to diverse change of air temperature, sea temperature, deferent seasons. And small coast target have various infrared feature according to diverse change of environment. In this various environment, it is very important thing that we analyze and classify targets from the clutters to improve target detection accuracy. Thus, we propose infrared feature learning algorithm through LSTM neural network and also propose CR-DuNN algorithm that integrate LSTM prediction network with Du-CNN classification network to classify targets from the clutters.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.3
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• pp.195-202
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• 1998

The LPCVD system of batch type for the massproduction of semiconductor fabrication has a problem of phosphorous concentration uniformity in the boat. In this paper we study an improvement of the uniformity for phosphorous concentration and sheet resistance. These property was improved by using the nitrogen process and modified long nozzle for gas injection tube in the doped polysilicon deposition system. The phosphorous concentration and its uniformity for polysilicon film are measured by XRF(X-ray Fluorescence) for the conventional process condition and nitrogen process. In conventional process condition, the phosphorous concentration, it uniformity and sheet resistance for polysilicon film are in the range of 3.8~5.4$\times$10\ulcorner atoms/㎤, 17.3% and 59~$\Omega$/ , respectively. For the case of nitrogen process the corresponding measurements exhibited between 4.3~5.3$\times$10\ulcorner atoms/㎤, 10.6% and 58~81$\Omega$/ . We find that in the nitrogen process the uniformity of phosphorous concentration improved compared with conventional process condition, however, the sheet resistance in the up zone of the boat increased about 12 $\Omega$/ . In modified long nozzle, the phosphorous concentration, its uniformity and sheet resistance for polysilicon films are in the range of 4.5~5.1$\times$10\ulcorner atoms/㎤, 5.3% and 60~65$\Omega$/ respectively. Annealing after $N_2$process gives the increment of grain size and the decrement of roughness. Modification of nozzle gives the increment of injection amount of PH$_3$. Both of these suggestion result in the stable phosphorous concentration and sheet resistance. The results obtained in this study are also applicable to process control of batch type system for memory device fabrication.

• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.25-30
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• 2013

In this work, we investigate the statistical properties of gamma exposure rates using well-known analysis methods, such as Autocorrelation Function Analysis(ACF), Rescaled Range Analysis(R/S Analysis), and Detrended Fluctuation Analysis(DFA). Especially, DFA is an important method to reliably detect long-range correlations in non-stationary time series. Our data are measured by Gangneung regional radiation monitoring station over the period of 1998 to 2011. First, we find a crossover indicating two different governing regimes in fluctuations of gamma exposure rates. Within a year, they show a strong long-ranged memory while this property vanishes over the range of time period longer than one year. Second, our finding is very securely supported by a variety of analysis tools. Those tools yield many relevant exponents which satisfies the well known relation between them.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• The Korean Journal of Physiology and Pharmacology
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• v.18 no.2
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• pp.135-141
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• 2014

The downregulation of A-type $K^+$ channels ($I_A$ channels) accompanying enhanced somatic excitability can mediate epileptogenic conditions in mammalian central nervous system. As $I_A$ channels are dominantly targeted by dendritic and postsynaptic processings during synaptic plasticity, it is presumable that they may act as cellular linkers between synaptic responses and somatic processings under various excitable conditions. In the present study, we electrophysiologically tested if the downregulation of somatic $I_A$ channels was sensitive to synaptic activities in young hippocampal neurons. In primarily cultured hippocampal neurons (DIV 6~9), the peak of $I_A$ recorded by a whole-cell patch was significantly reduced by high KCl or exogenous glutamate treatment to enhance synaptic activities. However, the pretreatment of MK801 to block synaptic NMDA receptors abolished the glutamate-induced reduction of the $I_A$ peak, indicating the necessity of synaptic activation for the reduction of somatic $I_A$. This was again confirmed by glycine treatment, showing a significant reduction of the somatic $I_A$ peak. Additionally, the gating property of $I_A$ channels was also sensitive to the activation of synaptic NMDA receptors, showing the hyperpolarizing shift in inactivation kinetics. These results suggest that synaptic LTP possibly potentiates somatic excitability via downregulating $I_A$ channels in expression and gating kinetics. The consequential changes of somatic excitability following the activity-dependent modulation of synaptic responses may be a series of processings for neuronal functions to determine outputs in memory mechanisms or pathogenic conditions.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.9
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• pp.783-787
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• 2002

In recent year, B $i_{4-}$x L $a_{x}$ $Ti_3$ $O_{12(BLT)}$ is one of promising substitute materials for the ferroelectric random access memory(FRAM) applications. But the systematic composition is still insufficient, so this experiment was carried out in ceramic ambient sintering process which has the very excellent ferroelectric property. Samples were prepared by a bulk and the purpose which was estimated with a suitability of thin films applications. The density of B $i_{3.75}$ L $a_{0.25}$ $Ti_3$ $O_{12}$ was high and the XRD pattern showed that the intensity of main peak (117) was increased at the argon ambient sintering. Controlling the quantity of oxygen, crystallization showed a thin, long plate like type, and we obtained the excellent dielectric and polarization properties at the argon atmosphere sintering. Also this sintering process was effective at the bulk sample. Argon ambient sintered sample produced higher permittivity of 154, the remanent polarization(2Pr) of 6.8 uC/$\textrm{cm}^2$ compared with that sintered in air and oxygen ambient. And this sintering process showed a possibility which could be applied to thin films process..

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.123-132
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• 2019

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.